What is Logistic Regression?

Logistic regression is the most widely used machine learning algorithm for classification problems. In its original form it is used for binary classification problem which has only two classes to predict. However with little extension and some human brain, logistic regression can easily be used for multi class classification problem. In this post I will be explaining about binary classification. I will also explain about the reason behind maximizing log likelihood function.

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What is Multicollinearity?

Multicollinearity occurs in a multi linear model where we have more than one predictor variables. So Multicollinearity exist when we can linearly predict one predictor variable (note not the target variable) from other predictor variables with significant degree of accuracy. It means two or more predictor variables are highly correlated. But not the vice versa means if there is low correlation among predictors then also multicollinearity may exist.

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What is stepAIC in R?

In R, stepAIC is one of the most commonly used search method for feature selection. We try to keep on minimizing the stepAIC value to come up with the final set of features. “stepAIC” does not necessarily means to improve the model performance, however it is used to simplify the model without impacting much on the performance. So AIC quantifies the amount of information loss due to this simplification. AIC stands for Akaike Information Criteria.

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Feature Selection Techniques in Regression Model

Feature selection is a way to reduce the number of features and hence reduce the computational complexity of the model. Many times feature selection becomes very useful to overcome with overfitting problem. It helps us in determining the smallest set of features that are needed to predict the response variable with high accuracy. if we ask the model, does adding new features, necessarily increase the model performance significantly? if not then why to add those new features which are only going to increase model complexity.

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Important Use Cases of NLP

In today’s world we are generating large amount of data every second. while tweeting, chating, writing or even speaking, we are fabricating corpse of data. Most of the data is in textual and unstructured form. Hence to make this data understandable by computer, we need to process it. NLP technique helps us in processing the data and helps us to get useful insights from it.

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Employee Attrition Rate Analysis – Insights from IBM HR Data

Storytelling or presenting insights is the most important part of data analytics. This is the selling point of all your hard work. Doesn’t matter how much hard work you have put in developing analytic model until you are able to get the attention of the target audience. Here in this particular article, my focus is on how we can use beautiful graphs to show the insights regarding employee attrition rate from IBM HR Attrition data. After all, a picture is worth to thousands of words.

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What is Linear Regression? Part:2

In any business there are some easy to measure variables like : Age, Gender, Income, Education Level etc. and there are some difficult to measure variables like amount of loan to give, no of days a patient will stay in the hospital, price of the house after 10 years etc. So Regression is the technique which enables you to determine difficult to measure variables with the help of easy to measure variables.

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Necessary Privileges for Creating Database Links

A database link is a pointer in the local database that lets you access objects on a remote database. To create a private database link, you must have been granted the proper privileges. The following table illustrates which privileges are required on which database for which type of link:

Privilege Database Required For
CREATE DATABASE LINK Local Creation of a private database link.
CREATE PUBLIC DATABASE LINK Local Creation of a public database link.
CREATE SESSION Remote Creation of any type of database link.

To see which privileges you currently have available, query ROLE_SYS_PRIVS. For example, you could create and execute the following privs.sql script (sample output included):

SELECT DISTINCT PRIVILEGE AS "Database Link Privileges"
FROM ROLE_SYS_PRIVS
WHERE PRIVILEGE IN ( 'CREATE SESSION','CREATE DATABASE LINK',
                     'CREATE PUBLIC DATABASE LINK')

or just execute following query to see all the permissions for current user:
SELECT DISTINCT PRIVILEGE AS "Database Link Privileges" FROM ROLE_SYS_PRIVS

Source: Oracle Docs

What is Lost Update Problem in DBMS?

In a schedule, if update performed by transaction T1 on data item ‘X’ gets overwritten by the update performed by transaction T2 on same data item ‘X’, then we say that update of T1 is lost to the update of T2.

This problem is known as Lost-Update-Problem in concurrent schedules.

Example:

with X = 50 and Y =50 (initial values)

T1T2
read(x) (T1I1)
x=x+10 (T1I2)
read(x) (T2I1)
x=x+20 (T2I2)
write(x) (T1I3)
read(y) (T1I4)
write(x) (T2I2)
commit (T2I2)
y=y+10 (T1I5)
write(y) (T1I6)
commit (T1I7)

Explanation:

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Serial Schedules, Concurrent Schedules and Conflict Operations

A schedule is the representation of execution sequence for all the instructions of the transactions. Schedules are categorized in two types:

  • Serial Schedules
  • Concurrent Schedules

Serial Schedules:

A schedule is said to be serial if and only if all the instructions of all the transactions get executed non-preemptively as an unit. OR

Each serial schedule consists of a sequence of instructions from various transactions, where the instructions belonging to one single transaction appear together in that schedule.

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Concurrent Execution in Transaction | DBMS

Transaction-processing systems usually allow multiple transactions to run concurrently. Allowing multiple transactions to update data concurrently causes several complications with consistency of the data.

Ensuring consistency in spite of concurrent execution of transactions requires extra work; it is far easier to insist that transactions run serially—that is, one at a time, each starting only after the previous one has completed.

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Difference between Normalization and Normal Forms

Normalization:

Normalization is the systematic process applied on the relations to reduce the degree of redundancy.

Normalization is defined as systematic because it always gives guarantee for following properties –

  • Lossless decomposition.
  • Dependency preservation.
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